Abstract: The IC-FAR project (2013-2016), funded by the Italian ministry of University, Research and Education, aims to use datasets from 16 Italian long term agronomic experiments (LTEs) to assess the reliability of different cropping system models over a range of Mediterranean environments and cropping systems. The selected models will be used for scenario and uncertainty analyses vs near-future climate change. The LTEs are located in seven sites: Turin, Padua, Bologna, Ancona, Pisa, Perugia, Foggia. The project’s is linked to international projects such as MACSUR, AgMIP, ANAEE, ESFRI and GRA, and has model developer teams as associate partners. IC-FAR is structured in five WPs. WP1 is focused on building a common dataset and sampling protocols.  The field data will be implemented in the WP2 to calibrate, validate and assess the performances of different models across Italian environments. An uncertainty analysis will be performed in relation to the model types, cropping system typologies and climate scenarios (WP3). WP4 and WP5 are focused on capacity building on modeling and on dissemination, including networking with other European LTE platforms (WP4), and to the project coordination (WP5). The next step of IC-FAR will be the design and realization of a special issue summarizing a selection of the most important results from the LTEs, that will be the starting point towards the full implementation of the data sharing policy of this project.

Abstract: The most important factors limiting the agriculture in Puglia region in Southern Italy are typically  linked to high temperatures and low water availability. In expected future scenarios, increased challenges about such factors could further limit the crop productivity. We adopted an approach based on the simulation analysis carried out through the DSSAT implemented into AEGIS/WIN. This tool has proved to be an useful tool to manage the analysis results about the potential future impact of two regionalized climatic scenarios within the SRES scenario A2. Anomaly2 and Anomaly5, based on a target increase of global temperature of 2° and 5°C.  The winter durum wheat and tomato were simulated on the basis of the interaction climate-soil on a regional scale framework interesting the whole area of Puglia (about 20000 km2) subdivided in about 200 units of simulation. The wheat yield has proved to be mainly affected by the variability of precipitation. Conversely, the largest increment of temperature of spring-summer period caused a tomato yield reduction. As second step, in order to individuate the optimal adaptation strategies for both crops, a spatial analysis focused on sowing/transplanting times, nitrogen fertilization and tomato-irrigation has been carried out. The results have clearly indicated the different sensitivity of crops to climate change as influenced by the specific interaction soil-climate and an high degree of uncertainty, especially for the sowing date, depending even on small differences related to the climatic differences characterizing the areas of the Puglia territory.

Abstract: • First model inter-comparison on crop rotations. • Continuous simulation of multi-year crop rotations yields outperformed single-year simulation. • Low accuracy of yield predictions in less commonly modelled crops such as potato, radish, grass vegetation. • Multi-model mean prediction was found to minimise the likely error arising from single-model predictions. • The representation of intermediate crops and carry-over effects in the models require further research efforts.
Diversification of crop rotations is considered an option to increase the resilience of European crop production under climate change. So far, however, many crop simulation studies have focused on predicting single crops in separate one-year simulations. Here, we compared the capability of fifteen crop growth simulation models to predict yields in crop rotations at five sites across Europe under minimal calibration. Crop rotations encompassed 301 seasons of ten crop types common to European agriculture and a diverse set of treatments (irrigation, fertilisation, CO2 concentration, soil types, tillage, residues, intermediate or catch crops). We found that the continuous simulation of multi-year crop rotations yielded results of slightly higher quality compared to the simulation of single years and single crops. Intermediate crops (oilseed radish and grass vegetation) were simulated less accurately than main crops (cereals). The majority of models performed better for the treatments of increased CO2 and nitrogen fertilisation than for irrigation and soil-related treatments. The yield simulation of the multi-model ensemble reduced the error compared to single-model simulations. The low degree of superiority of continuous simulations over single year simulation was caused by (a) insufficiently parameterised crops, which affect the performance of the following crop, and (b) the lack of growth-limiting water and/or nitrogen in the crop rotations under investigation. In order to achieve a sound representation of crop rotations, further research is required to synthesise existing knowledge of the physiology of intermediate crops and of carry-over effects from the preceding to the following crop, and to implement/improve the modelling of processes that condition these effects.